What is AGISystem2 (UBH NL)?
AGISystem2 (UBH NL) is an AI research platform inspired by the System 2 concept from cognitive psychology—the slow, deliberate, logical mode of human reasoning (as opposed to System 1's fast, intuitive responses). The platform brings together formal verification, neural-symbolic hybrid reasoning, and a minimal Boolean substrate.
A key innovation is the introduction of a Controlled Natural Language (CNL) and a matched semantic programming language (DSL) that give formal, machine-verifiable meaning to structured fragments of language. Instead of teaching humans to write in formal logic, we utilize a language that captures the semantic structure implicit in common reasoning patterns. The result is machine-checkable reasoning over formally modeled content, backed by mathematical proofs and deterministic evaluation.
The Vision: Universal Reasoning System
AGISystem2 (UBH NL) is driven by a core hypothesis: a plausible route toward "real" AGI goes through the ability to represent and manipulate theories as computational objects—compositional, queryable, checkable, and revisable.
We utilize a Universal Boolean Hypergraph (UBH) as a minimal trusted kernel. By lowering complex domain problems—be they medical, legal, or scientific—down to this universal substrate of bits and gates, we gain absolute auditability. The system does not "guess"; it solves for consistency and returns checkable certificates.
Vision Roadmap
Capability map and research goals for the Universal Reasoning System.
System 2 + LLM
Using LLMs as creative proposers and UBH NL as the rigorous logical judge.
What You Can Do With It (Today)
Build checkable micro-theories
Encode structured facts and rules in CNL, query/prove them, and get explainable traces. This is the "unit of progress": small theories that are executable, inspectable, and testable.
Verify logical consistency
Detect contradictions across multiple regulatory documents or scientific papers. The system flags exactly which rules are mutually exclusive.
Use LLMs safely
LLMs can propose theory fragments or plans. AGISystem2’s job is to validate and harden those proposals with proofs, counterexamples, and reproducible workflows.
Why This Matters
For applications where verification is critical—compliance, medical decisions, legal reasoning, safety-critical systems—probabilistic pattern matching alone isn't enough. AGISystem2 (UBH NL) provides:
- Proof traces: Every conclusion traces back to facts and rules via origin tracking.
- Contradiction detection: The system identifies and explains inconsistencies in knowledge.
- Reproducible results: Deterministic parsing and solving ensure the same input always produces the same output.
- Checkable evidence: Results are only accepted when accompanied by a witness or a certificate.
Capability Comparison
| Approach | Strength | Gap |
|---|---|---|
| LLM-only | Fast synthesis, broad language coverage | Difficult to verify; prone to hallucinations and logical gaps |
| Traditional SAT/SMT | Strong correctness guarantees | Hard to connect to natural language and domain knowledge |
| AGISystem2 (UBH NL) | Executable DSL + deterministic CNL + minimal trusted kernel | Focuses on structured reasoning; open-ended chat is out of scope |
Scope & Honesty
What AGISystem2 (UBH NL) does well:
- Taxonomic reasoning and rule-based inference.
- Explicit contradiction detection within formalized domains.
- Generating checkable proof certificates for every conclusion.
What it does NOT do:
- Open-ended conversation or emotional intelligence.
- Automatically "knowing" a domain without explicit modeling effort.
Fundamental limitation: The system reasons correctly within a theory, but cannot guarantee the theory itself is correct.
Foundational Principles
The UBHNL paradigm is governed by three non-negotiable architectural axioms. Radical Minimalism ensures the trusted kernel remains small enough for formal audit. The principle of Result Verification mandates that every claim must be supported by a checkable witness or certificate. Finally, Semantic Isomorphism provides a unified representation where natural-sounding language (CNL) and machine-efficient code (DSL) are mathematically identical, ensuring that human intent and machine execution are perfectly aligned.